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基于单个传感器的实时连续步态阶段和速度估计

Real-Time Continuous Gait Phase and Speed Estimation from a Single Sensor.

作者信息

Quintero David, Lambert Daniel J, Villarreal Dario J, Gregg Robert D

机构信息

Department of Mechanical Engineering, University of Texas at Dallas, Richardson, TX 75080.

Department of Bioengineering, University of Texas at Dallas, Richardson, TX 75080.

出版信息

Control Technol Appl. 2017 Aug;2017:847-852. doi: 10.1109/CCTA.2017.8062565. Epub 2017 Oct 9.

Abstract

Human gait involves a repetitive cycle of movements, and the phase of gait represents the location in this cycle. Gait phase is measured across many areas of study (e.g., for analyzing gait and controlling powered lower-limb prosthetic and orthotic devices). Current gait phase detection methods measure discrete gait events (e.g., heel strike, flat foot, toe off, etc.) by placing multiple sensors on the subject's lower-limbs. Using multiple sensors can create difficulty in experimental setup and real-time data processing. In addition, detecting only discrete events during the gait cycle limits the amount of information available during locomotion. In this paper we propose a real-time and continuous measurement of gait phase parameterized by a mechanical variable (i.e., phase variable) from a single sensor measuring the human thigh motion. Human subject experiments demonstrate the ability of the phase variable to accurately parameterize gait progression for different walking/running speeds (1 to 9 miles/hour). Our results show that this real-time method can also estimate gait speed from the same sensor.

摘要

人类步态涉及一系列重复的运动周期,步态阶段代表了该周期中的位置。步态阶段在许多研究领域都有测量(例如,用于分析步态以及控制动力下肢假肢和矫形器)。当前的步态阶段检测方法通过在受试者下肢放置多个传感器来测量离散的步态事件(例如,脚跟触地、平足、脚趾离地等)。使用多个传感器会给实验设置和实时数据处理带来困难。此外,仅检测步态周期中的离散事件会限制运动过程中可用的信息量。在本文中,我们提出了一种通过测量人体大腿运动的单个传感器,以机械变量(即相位变量)对步态阶段进行实时连续测量的方法。人体实验证明了相位变量能够针对不同的步行/跑步速度(1至9英里/小时)准确地对步态进展进行参数化。我们的结果表明,这种实时方法还可以从同一个传感器估计步态速度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4363/6105289/b501b2df92f4/nihms878240f1.jpg

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